Estimation of Stature using Lower Limb Dimensions among Adolescent Population of Kolkata: A Cross-sectional Study

Abstract

Introduction: Apart from age, sex and racial affiliation, estimation of stature from human extremities is an important step in developing a biological profile for identification of an unknown individual especially when the body found is either dismembered, mutilated, or disfigured. Stature estimation plays an important role in developing a biological profile for human identification and provides as a valuable indicator for an unknown individual in a population. Aim: To identify stature using various lower limb dimensions. Materials and Methods: This analytical, cross-sectional study was conducted at Kolkata based school from March 2019 to September 2019 amongst 120 adolescent school going boys aged 10-16 yrs of age. The lower limb length, knee height, navicular height, foot length and foot breadth were taken by using standard anthropometric procedures. Pearson correlation coefficient was used for assessing relationship between stature and various lower limb dimensions. Significance of differences was tested using independent t-test. Results: This study showed that all variables of both right and left side were significant predictors of stature (p<0.01).While taking the prediction accuracy, lower limb length (right, R2=89.7%, and left, R2=89.7%), knee height (right, R2=55.4%, and left, R2=55.5%), foot breadth (right, R2=58.0%, and left, R2=56.8%) provided the highest prediction accuracy for stature. Following multivariate linear regression model, only four variables- lower limb length (both right and left side), foot breadth (both right and left side) significantly (p<0.001) contributed to prediction model for stature with the use of regression equations. Conclusion: All variables (lower limb length, knee height, foot length and breadth, navicular height) were found to be statistically significant predictors of stature. Amongst all these variables lower limb length, knee height and foot breadth provided highest prediction accuracy. These measurements of lower limbs and regression equations can be used for identification of unknown human remains, particularly in cases of dismembered bodies.